The original Diagnosis-Related Group (DRG) patient classification system was created to identify groups of hospital inpatients who were similar with respect to both clinical condition and average length of stay. Recently, a new DRG system was created using the same statistical techniques, but different clinical input. A Primary objective of this new system was to improve the clinical homogeneity of patients within individual DRGs, while maintaining the system's ability to identify groups of patients with similar lengths of stay. The first phase of this project will measure the improvement in the new DRG system by comparing the ability of the two DRG systems to explain variation in two measures of resource use -- average length of stay and average cost per case. By directly comparing the estimated mean squares for each DRG system, we will determine: a) which DRG system explains the most variance, b) on average, which DRG system explains the most variance per DRG, and c) whether the new DRG system reduces variance in a statistically significant sense. The second phase of this project will identify individual DRGs in the new system that can be most significantly improved by further accounting for clinical condition. Disease Staging, an alternative patient classification system, will be used to further differentiate patients within individual DRGs. Every DRG in which a significant reduction in variance occurs, as measured by the F-test, will identified as a potential candidate for further improvement in clinical homogeneity. Those DRGs which achieve the greatest reduction in variance, as measured by adjusted R2, will be considered the most clinically heterogeneous. The results of this project will provide researchers and regulators with information concerning the extent to which the new DRG system has benefitted from improved clinical input, as well as the extent to which individual DRGs can be further improved using clinical information which is readily available from existing patient discharge abstracts.